Thin films of (Cu2S)100-x( SnS2 )x at X=[ 30,40, &50)]% with thickness (0.9±0.03)µm , had been prepared by chemical spray pyrolysis method on glass substrates at 573 K. These films were then annealed under low pressure of(10-2) mbar ,373)423&473)K for one hour . This research includes , studying the the optical properties of (Cu2S)100-x-(SnS2)x at X=[ 30,40, &50)]% .Moreover studying the effect of annealing on their optical properties , in order to fabricate films with high stability and transmittance that can be used in solar cells. The transmittance and absorbance spectra had been recorded in the wavelength range (310 - 1100) nm in order to study the optical properties . It was found that these films had direct optical band

Nano-structural of vanadium pentoxide (V2O5) thin films were
deposited by chemical spray pyrolysis technique (CSPT). Nd and Ce
doped vanadium oxide films were prepared, adding Neodymium
chloride (NdCl3) and ceric sulfate (Ce(SO4)2) of 3% in separate
solution. These precursor solutions were used to deposit un-doped
V2O5 and doped with Nd and Ce films on the p-type Si (111) and
glass substrate at 250°C. The structural, optical and electrical
properties were investigated. The X-ray diffraction study revealed a
polycrystalline nature of the orthorhombic structure with the
preferred orientation of (010) with nano-grains. Atomic force
microscopy (AFM) was used to characterize the morphology of the
films. Un-do

The influence of the reaction gas composition during the DC magnetron sputtering process on the structural, chemical and optical properties of Ce-oxide thin films was investigated. X-ray diffraction (XRD) studies confirmed that all thin films exhibited a polycrystalline character with cubic fluorite structure for cerium dioxide. X-ray photoelectron spectroscopy (XPS) analyses revealed that cerium is present in two oxidation states, namely as CeO2 and Ce2O3, at the surface of the films prepared at oxygen/argon flow ratios between 0% and 7%, whereas the films are completely oxidized into CeO2 as the aforementioned ratio increases beyond 14%. Various optical parameters for the thin films (including an optical band gap in the range of 2.25–3.

This paper presents the study and analysis, analytically and numerical of circular cylindrical shell pipe model, under variable loads, transmit fluid at the high velocity state (fresh water). The analytical analysis depended on the energy observation principle (Hamilton Principle), where divided all energy in the model to three parts , strain energy, kinetic energy and transmitted energy between flow and solid (kinetic to potential energy). Also derive all important equations for this state and approach to final equation of motion, free and force vibration also derived. the relations between the displacement of model function of velocity of flow, length of model, pipe thickness, density of flowed with location coordinate x-axis and angle

Determining the face of wearing a mask from not wearing a mask from visual data such as video and still, images have been a fascinating research topic in recent decades due to the spread of the Corona pandemic, which has changed the features of the entire world and forced people to wear a mask as a way to prevent the pandemic that has calmed the entire world, and it has played an important role. Intelligent development based on artificial intelligence and computers has a very important role in the issue of safety from the pandemic, as the Topic of face recognition and identifying people who wear the mask or not in the introduction and deep education was the most prominent in this topic. Using deep learning techniques and the YOLO (”You on

Skull image separation is one of the initial procedures used to detect brain abnormalities. In an MRI image of the brain, this process involves distinguishing the tissue that makes up the brain from the tissue that does not make up the brain. Even for experienced radiologists, separating the brain from the skull is a difficult task, and the accuracy of the results can vary quite a little from one individual to the next. Therefore, skull stripping in brain magnetic resonance volume has become increasingly popular due to the requirement for a dependable, accurate, and thorough method for processing brain datasets. Furthermore, skull stripping must be performed accurately for neuroimaging diagnostic systems since neither non-brain tissues nor

   Predicting permeability is a cornerstone of petroleum reservoir engineering, playing a vital role in optimizing hydrocarbon recovery strategies. This paper explores the application of neural networks to predict permeability in oil reservoirs, underscoring their growing importance in addressing traditional prediction challenges. Conventional techniques often struggle with the complexities of subsurface conditions, making innovative approaches essential. Neural networks, with their ability to uncover complicated patterns within large datasets, emerge as a powerful alternative. The Quanti-Elan model was used in this study to combine several well logs for mineral volumes, porosity and water saturation estimation. This model goes be